The Impact of Prophylactic HPV Vaccination on the Incidence of High-Grade Cervical Intraepithelial Neoplasia (CIN2/CIN3): A Systematic Review
Bibliographic record
Abstract
Introduction: Cervical cancer is the fourth most common cancer in women globally, etiologically linked to persistent high-risk human papillomavirus (HPV) infection (World Health Organization, 2024a; World Health Organization, 2024b). High-grade cervical intraepithelial neoplasia (CIN), specifically CIN2 and CIN3, are the direct, histologically confirmed precursor lesions (Cleveland Clinic, 2023). This systematic review synthesizes the evidence from randomized controlled trials (RCTs) and real-world observational studies on the effectiveness of prophylactic HPV vaccination in reducing the incidence of CIN2 and CIN3 (CIN2+). Methods: Following PRISMA guidelines, a systematic search of PubMed, Embase, and the Cochrane Library was conducted (Ghebrekidan et al., 2024; Khalil et al., 2023). Studies were included if they were RCTs or observational (cohort, case-control) studies assessing the efficacy or effectiveness of prophylactic HPV vaccination (bivalent, quadrivalent, or nonavalent) on histologically confirmed CIN2+ outcomes in females. Methodological quality was appraised using the Cochrane Risk of Bias 2 (RoB 2) tool for RCTs (Sterne et al., 2019; Cochrane, 2024) and the Newcastle-Ottawa Scale (NOS) for observational studies (Wells et al., 2024; Ohri, 2024). Results: This synthesis includes 17 high-quality studies. Foundational RCTs (e.g., FUTURE, PATRICIA) demonstrated near-perfect efficacy (98-100%) against vaccine-type HPV 16/18-related CIN2+ in per-protocol (HPV-naïve) populations (FUTURE II Study Group, 2007; Paavonen et al., 2009; Kjaer et al., 2018). A high-certainty Cochrane review confirmed a 63% reduction in any CIN2+ (irrespective of HPV type) in hrHPV-negative young women (Risk Ratio 0.37, 95% CI 0.25-0.55) (Arbyn et al., 2018). Recent, large-scale real-world effectiveness (RWE) studies from national registries report profound, significant reductions in high-grade lesions. In England, cohorts vaccinated at age 12-13 showed an 87% reduction in invasive cervical cancer and a 97% reduction in CIN3 (Falcaro et al., 2021). In Sweden, vaccination before age 17 was associated with an 88% reduction in invasive cervical cancer (Lei et al., 2020), and in Scotland, an 86% reduction in CIN3+ was observed in the 12-13 age cohort (Palmer et al., 2019). Effectiveness is strongly dependent on vaccination age (Hariri et al., 2023; Herweijer et al., 2016). Furthermore, significant evidence demonstrates high effectiveness (74-87% reduction) in preventing the recurrence of high-grade lesions when used as an adjuvant to surgical conization (Dvořák et al., 2024; Ghelardi et al., 2021). Discussion: The evidence is overwhelming and consistent. The near-100% efficacy observed in controlled trial settings has translated directly into profound population-level effectiveness in countries with high, sustained vaccine uptake (Ghebrekidan et al., 2024; Drolet et al., 2019). The dependency of effectiveness on age confirms the vaccine's prophylactic mechanism, underscoring the criticality of pre-adolescent vaccination. Conclusion: Prophylactic HPV vaccination provides a significant, robust, and long-lasting reduction in the incidence of high-grade cervical precancer (CIN2/3). High-coverage national programs are demonstrating the potential to "almost eliminate" (Falcaro et al., 2021) cervical cancer in vaccinated generations, representing a major public health triumph.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.010 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".